Experimental dataset to develop a parametric model based of DC geared motor in feeder machine

This paper presents the application of a System Identification based on Particle Swarm Optimization (PSO) technique to develop parametric model of experimental dataset of DC geared motor in feeder machine. The experiment was conducted to measure the input (voltage) and output (voltage) data. The act...

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Main Authors: Azlan, W. M, Salleh, S. M, Mahzan, S, Sadikin, A, Ahmad, S
Format: Article
Published: Institute of Advanced Engineering and Science (IAES) 2019
Subjects:
Online Access:http://eprints.uthm.edu.my/3757/
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author Azlan, W. M
Salleh, S. M
Mahzan, S
Sadikin, A
Ahmad, S
author_facet Azlan, W. M
Salleh, S. M
Mahzan, S
Sadikin, A
Ahmad, S
author_sort Azlan, W. M
building UTHM Institutional Repository
collection Online Access
description This paper presents the application of a System Identification based on Particle Swarm Optimization (PSO) technique to develop parametric model of experimental dataset of DC geared motor in feeder machine. The experiment was conducted to measure the input (voltage) and output (voltage) data. The actual data is used to be optimized using PSO algorithm. The parameter emphasized is time, mean square error (mse) and average time. One of the best models has been chosen based on the optimum parameters.
first_indexed 2025-11-15T20:05:00Z
format Article
id uthm-3757
institution Universiti Tun Hussein Onn Malaysia
institution_category Local University
last_indexed 2025-11-15T20:05:00Z
publishDate 2019
publisher Institute of Advanced Engineering and Science (IAES)
recordtype eprints
repository_type Digital Repository
spelling uthm-37572021-11-22T02:20:42Z http://eprints.uthm.edu.my/3757/ Experimental dataset to develop a parametric model based of DC geared motor in feeder machine Azlan, W. M Salleh, S. M Mahzan, S Sadikin, A Ahmad, S QC Physics This paper presents the application of a System Identification based on Particle Swarm Optimization (PSO) technique to develop parametric model of experimental dataset of DC geared motor in feeder machine. The experiment was conducted to measure the input (voltage) and output (voltage) data. The actual data is used to be optimized using PSO algorithm. The parameter emphasized is time, mean square error (mse) and average time. One of the best models has been chosen based on the optimum parameters. Institute of Advanced Engineering and Science (IAES) 2019 Article PeerReviewed Azlan, W. M and Salleh, S. M and Mahzan, S and Sadikin, A and Ahmad, S (2019) Experimental dataset to develop a parametric model based of DC geared motor in feeder machine. International Journal of Electrical and Computer Engineering (IJECE), 9 (3). pp. 1-5. ISSN 2088-8708 http://doi.org/10.11591/ijece.v9i3.pp1576-1584
spellingShingle QC Physics
Azlan, W. M
Salleh, S. M
Mahzan, S
Sadikin, A
Ahmad, S
Experimental dataset to develop a parametric model based of DC geared motor in feeder machine
title Experimental dataset to develop a parametric model based of DC geared motor in feeder machine
title_full Experimental dataset to develop a parametric model based of DC geared motor in feeder machine
title_fullStr Experimental dataset to develop a parametric model based of DC geared motor in feeder machine
title_full_unstemmed Experimental dataset to develop a parametric model based of DC geared motor in feeder machine
title_short Experimental dataset to develop a parametric model based of DC geared motor in feeder machine
title_sort experimental dataset to develop a parametric model based of dc geared motor in feeder machine
topic QC Physics
url http://eprints.uthm.edu.my/3757/
http://eprints.uthm.edu.my/3757/